import sys, os, asyncio
import traceback
from dotenv import load_dotenv

load_dotenv()
import os, io

sys.path.insert(
    0, os.path.abspath("../..")
)  # Adds the parent directory to the system path
import pytest
import litellm
from litellm import (
    embedding,
    completion,
    text_completion,
    completion_cost,
    atext_completion,
    TextCompletionResponse,
)
from litellm import RateLimitError

litellm.num_retries = 3


token_prompt = [
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def test_unit_test_text_completion_object():
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                    ],
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        ],
        "created": 1712163061,
        "model": "ft:babbage-002:ai-r-d-zapai:v3-fields-used:84jb9rtr",
        "object": "text_completion",
        "system_fingerprint": None,
        "usage": {"completion_tokens": 54, "prompt_tokens": 1877, "total_tokens": 1931},
    }

    text_completion_obj = TextCompletionResponse(**openai_object)

    ## WRITE UNIT TESTS FOR TEXT_COMPLETION_OBJECT
    assert text_completion_obj.id == "cmpl-99y7B2svVoRWe1xd7UFRmeGjZrFSh"
    assert text_completion_obj.object == "text_completion"
    assert text_completion_obj.created == 1712163061
    assert (
        text_completion_obj.model
        == "ft:babbage-002:ai-r-d-zapai:v3-fields-used:84jb9rtr"
    )
    assert text_completion_obj.system_fingerprint == None
    assert len(text_completion_obj.choices) == len(openai_object["choices"])

    # TEST FIRST CHOICE #
    first_text_completion_obj = text_completion_obj.choices[0]
    assert first_text_completion_obj.index == 0
    assert first_text_completion_obj.logprobs.text_offset == [101]
    assert first_text_completion_obj.logprobs.tokens == ["0"]
    assert first_text_completion_obj.logprobs.token_logprobs == [-0.00023488728]
    assert len(first_text_completion_obj.logprobs.top_logprobs) == len(
        openai_object["choices"][0]["logprobs"]["top_logprobs"]
    )
    assert first_text_completion_obj.text == "0"
    assert first_text_completion_obj.finish_reason == "length"

    # TEST SECOND CHOICE #
    second_text_completion_obj = text_completion_obj.choices[1]
    assert second_text_completion_obj.index == 1
    assert second_text_completion_obj.logprobs.text_offset == [116]
    assert second_text_completion_obj.logprobs.tokens == ["0"]
    assert second_text_completion_obj.logprobs.token_logprobs == [-0.013745008]
    assert len(second_text_completion_obj.logprobs.top_logprobs) == len(
        openai_object["choices"][0]["logprobs"]["top_logprobs"]
    )
    assert second_text_completion_obj.text == "0"
    assert second_text_completion_obj.finish_reason == "length"

    # TEST LAST CHOICE #
    last_text_completion_obj = text_completion_obj.choices[-1]
    assert last_text_completion_obj.index == 53
    assert last_text_completion_obj.logprobs.text_offset == [143]
    assert last_text_completion_obj.logprobs.tokens == ["0"]
    assert last_text_completion_obj.logprobs.token_logprobs == [-0.0012339224]
    assert len(last_text_completion_obj.logprobs.top_logprobs) == len(
        openai_object["choices"][0]["logprobs"]["top_logprobs"]
    )
    assert last_text_completion_obj.text == "0"
    assert last_text_completion_obj.finish_reason == "length"

    assert text_completion_obj.usage.completion_tokens == 54
    assert text_completion_obj.usage.prompt_tokens == 1877
    assert text_completion_obj.usage.total_tokens == 1931


def test_completion_openai_prompt():
    try:
        print("\n text 003 test\n")
        response = text_completion(
            model="gpt-3.5-turbo-instruct",
            prompt=["What's the weather in SF?", "How is Manchester?"],
        )
        print(response)
        assert len(response.choices) == 2
        response_str = response["choices"][0]["text"]
    except Exception as e:
        pytest.fail(f"Error occurred: {e}")


# test_completion_openai_prompt()


def test_completion_openai_engine_and_model():
    try:
        print("\n text 003 test\n")
        litellm.set_verbose = True
        response = text_completion(
            model="gpt-3.5-turbo-instruct",
            engine="anything",
            prompt="What's the weather in SF?",
            max_tokens=5,
        )
        print(response)
        response_str = response["choices"][0]["text"]
        # print(response.choices[0])
        # print(response.choices[0].text)
    except Exception as e:
        pytest.fail(f"Error occurred: {e}")


# test_completion_openai_engine_and_model()


def test_completion_openai_engine():
    try:
        print("\n text 003 test\n")
        litellm.set_verbose = True
        response = text_completion(
            engine="gpt-3.5-turbo-instruct",
            prompt="What's the weather in SF?",
            max_tokens=5,
        )
        print(response)
        response_str = response["choices"][0]["text"]
        # print(response.choices[0])
        # print(response.choices[0].text)
    except Exception as e:
        pytest.fail(f"Error occurred: {e}")


# test_completion_openai_engine()


def test_completion_chatgpt_prompt():
    try:
        print("\n gpt3.5 test\n")
        response = text_completion(
            model="gpt-3.5-turbo", prompt="What's the weather in SF?"
        )
        print(response)
        response_str = response["choices"][0]["text"]
        print("\n", response.choices)
        print("\n", response.choices[0])
        # print(response.choices[0].text)
    except Exception as e:
        pytest.fail(f"Error occurred: {e}")


# test_completion_chatgpt_prompt()


def test_text_completion_basic():
    try:
        print("\n test 003 with logprobs \n")
        litellm.set_verbose = False
        response = text_completion(
            model="gpt-3.5-turbo-instruct",
            prompt="good morning",
            max_tokens=10,
            logprobs=10,
        )
        print(response)
        print(response.choices)
        print(response.choices[0])
        # print(response.choices[0].text)
        response_str = response["choices"][0]["text"]
    except Exception as e:
        pytest.fail(f"Error occurred: {e}")


# test_text_completion_basic()


def test_completion_text_003_prompt_array():
    try:
        litellm.set_verbose = False
        response = text_completion(
            model="gpt-3.5-turbo-instruct",
            prompt=token_prompt,  # token prompt is a 2d list
        )
        print("\n\n response")

        print(response)
        # response_str = response["choices"][0]["text"]
    except Exception as e:
        pytest.fail(f"Error occurred: {e}")


# test_completion_text_003_prompt_array()


# not including this in our ci cd pipeline, since we don't want to fail tests due to an unstable replit
# def test_text_completion_with_proxy():
#     try:
#         litellm.set_verbose=True
#         response = text_completion(
#             model="facebook/opt-125m",
#             prompt='Write a tagline for a traditional bavarian tavern',
#             api_base="https://openai-proxy.berriai.repl.co/v1",
#             custom_llm_provider="openai",
#             temperature=0,
#             max_tokens=10,
#         )
#         print("\n\n response")

#         print(response)
#     except Exception as e:
#         pytest.fail(f"Error occurred: {e}")
# test_text_completion_with_proxy()


##### hugging face tests
def test_completion_hf_prompt_array():
    try:
        litellm.set_verbose = True
        print("\n testing hf mistral\n")
        response = text_completion(
            model="huggingface/mistralai/Mistral-7B-v0.1",
            prompt=token_prompt,  # token prompt is a 2d list,
            max_tokens=0,
            temperature=0.0,
            # echo=True, # hugging face inference api is currently raising errors for this, looks like they have a regression on their side
        )
        print("\n\n response")

        print(response)
        print(response.choices)
        assert len(response.choices) == 2
        # response_str = response["choices"][0]["text"]
    except Exception as e:
        print(str(e))
        if "is currently loading" in str(e):
            return
        if "Service Unavailable" in str(e):
            return
        pytest.fail(f"Error occurred: {e}")


# test_completion_hf_prompt_array()


def test_text_completion_stream():
    try:
        response = text_completion(
            model="huggingface/mistralai/Mistral-7B-v0.1",
            prompt="good morning",
            stream=True,
            max_tokens=10,
        )
        for chunk in response:
            print(f"chunk: {chunk}")
    except Exception as e:
        pytest.fail(f"GOT exception for HF In streaming{e}")


# test_text_completion_stream()

# async def test_text_completion_async_stream():
#     try:
#         response = await atext_completion(
#                 model="text-completion-openai/gpt-3.5-turbo-instruct",
#                 prompt="good morning",
#                 stream=True,
#                 max_tokens=10,
#             )
#         async for chunk in response:
#             print(f"chunk: {chunk}")
#     except Exception as e:
#         pytest.fail(f"GOT exception for HF In streaming{e}")

# asyncio.run(test_text_completion_async_stream())


def test_async_text_completion():
    litellm.set_verbose = True
    print("test_async_text_completion")

    async def test_get_response():
        try:
            response = await litellm.atext_completion(
                model="gpt-3.5-turbo-instruct",
                prompt="good morning",
                stream=False,
                max_tokens=10,
            )
            print(f"response: {response}")
        except litellm.Timeout as e:
            print(e)
        except Exception as e:
            print(e)

    asyncio.run(test_get_response())


def test_async_text_completion_together_ai():
    litellm.set_verbose = True
    print("test_async_text_completion")

    async def test_get_response():
        try:
            response = await litellm.atext_completion(
                model="together_ai/codellama/CodeLlama-13b-Instruct-hf",
                prompt="good morning",
                max_tokens=10,
            )
            print(f"response: {response}")
        except litellm.Timeout as e:
            print(e)
        except Exception as e:
            pytest.fail("An unexpected error occurred")

    asyncio.run(test_get_response())


# test_async_text_completion()


def test_async_text_completion_stream():
    # tests atext_completion + streaming - assert only one finish reason sent
    litellm.set_verbose = False
    print("test_async_text_completion with stream")

    async def test_get_response():
        try:
            response = await litellm.atext_completion(
                model="gpt-3.5-turbo-instruct",
                prompt="good morning",
                stream=True,
            )
            print(f"response: {response}")

            num_finish_reason = 0
            async for chunk in response:
                print(chunk)
                if chunk["choices"][0].get("finish_reason") is not None:
                    num_finish_reason += 1
                    print("finish_reason", chunk["choices"][0].get("finish_reason"))

            assert (
                num_finish_reason == 1
            ), f"expected only one finish reason. Got {num_finish_reason}"
        except Exception as e:
            pytest.fail(f"GOT exception for gpt-3.5 instruct In streaming{e}")

    asyncio.run(test_get_response())


# test_async_text_completion_stream()


@pytest.mark.asyncio
async def test_async_text_completion_chat_model_stream():
    try:
        response = await litellm.atext_completion(
            model="gpt-3.5-turbo",
            prompt="good morning",
            stream=True,
            max_tokens=10,
        )

        num_finish_reason = 0
        chunks = []
        async for chunk in response:
            print(chunk)
            chunks.append(chunk)
            if chunk["choices"][0].get("finish_reason") is not None:
                num_finish_reason += 1

        assert (
            num_finish_reason == 1
        ), f"expected only one finish reason. Got {num_finish_reason}"
        response_obj = litellm.stream_chunk_builder(chunks=chunks)
        cost = litellm.completion_cost(completion_response=response_obj)
        assert cost > 0
    except Exception as e:
        pytest.fail(f"GOT exception for gpt-3.5 In streaming{e}")


# asyncio.run(test_async_text_completion_chat_model_stream())
